Program Homework Implementation of the Improved Spread Spectrum Watermarking System

Reference Ingemar J. Cox, Joe Kilian, F. Tomson Leighton, and Talal Shamoon, “Secure Spread Spectrum Watermarking for Multimedia,” IEEE Trans. On Image Processing, vol. 6, no. 12, December 1997 H. S. Marvar and A. F. Florencio, "Improved Spread Spectrum: A New Modulation Technique for Robust Watermarking," IEEE Trans. on Signal Processing, vol. 51, no. 4, April 2003

Basic Knowledge 2-D DCT DCT pattern for an 8x8 block https://en.wikipedia.org/wiki/Discrete_cosine_transform Middle Band Low Band High Band

Spread-Spectrum Watermarking

Spread Spectrum General form Note: This notation is a little different from Cox 1997, “Secure Spread Spectrum Watermarking for multimedia” To match this form to Cox 1997 V, X are respect to x, u u = ( 0 ⋯ 𝑖 𝑡ℎ 𝑏𝑖𝑔𝑒𝑠𝑡 𝐷𝐶𝑇 𝑣𝑎𝑙𝑢𝑒 =𝑋(𝑖) ⋯ 0 )T b=1

Spread Spectrum Define The watermark W = b1 b2 … bn ( ex. n = 1000 ) bi ~ N(0,1) Use Sign(.) to convert bi into 1 or -1 The Cover Image C is transformed by N×N DCT. Ct=DCT(C). The coefficients to be altered X = x1 x2 … xm (m coefficients in the Ct except DC, m: extract pattern length) How to choose X: many heuristics In zigzag order choose an interval length = m Max m coefficients in zigzag order Random sample m coefficients m coefficients with largest DCT value …

Spread Spectrum Define The scaling parameter α (e.g. α = 0.1~100 ?) Extract pattern: 𝑢 = ( ±1 ⋮ ±1 ), Length of 𝑢 = m 𝑢 can be generate by an N(0,1) + sign(.) We can use 𝑢 to spread b into many frequency band and extract it from embedded image

Spread Spectrum Basic Idea 𝑠 = 𝑥 + α * b * 𝑢 𝑠 : watermarked signal 𝑥 : original signal α: scaling factor for watermark strength b: watermark bit (±1) 𝑢 : extract pattern ( ±1 ⋮ ±1 ) Use 𝑢 to spread signal b into many frequency band In this talk we take s = x + α * b * 𝑢 for example As you know si = xi(1+ α * b * 𝑢 𝑖 ) can also be our embedding method!!

Spread Spectrum Embedding Illustrate Given an image I Transform color domain from rgb to ycbcr, and then we chose y channel to embed our watermark Perform 2-D DCT to y channel Chose m elements from middle band to get 𝑥 Middle Band = 𝑥 Low Band High Band 𝑥 = ( 𝑥 1 ⋮ 𝑥 𝑚 )

Spread Spectrum Embedding Illustrate Given an Watermarking bit b Use pattern 𝑢 to spread b’s information into many frequency band 𝑠 = 𝑥 + α * b * 𝑢 Where 𝑠 = ( 𝑠 1 ⋮ 𝑠 𝑚 ) 𝑥 =( 𝑥 1 ⋮ 𝑥 𝑚 ) 𝑢 =( ±1 ⋮ ±1 ) α = 0.1~100 b = ±1

Spread Spectrum Extracting Illustrate Given a watermarked I Transform color domain from rgb to ycbcr, and then we chose y channel to extract our watermark Perform 2-D DCT to y channel Chose m elements(the same elements in embedding process) from middle band to get 𝑠 Middle Band = 𝑠 Low Band High Band 𝑠 = ( 𝑠 1 ⋮ 𝑠 𝑚 )

Spread Spectrum Extracting Illustrate Recall: Embedding function Calculate similarity sim = 𝑠 , 𝑢 𝑢 , 𝑢 Ideal case 𝑥 , 𝑢 =0 We can get sim = α * b * 𝑢 , 𝑢 𝑢 , 𝑢 = α * b Use sign(sim) to extract watermark bit b

Spread Spectrum So far, we can embed just “1” bit message into image But, how can we embed “n” bits? 3 Ways Code division Use different extract pattern(orthogonal extract patterns are suggest) Frequency division Embed message into different frequency band Spatial division Slice image into many blocks each block embeds 1 bit message

Improved Spread-Spectrum Watermarking

Improved Spread Spectrum Define The watermark W = b1 b2 … bn ( ex. n = 1000 ) bi ~ N(0,1) Use Sign(.) to convert bi into 1 or -1 The Cover Image C is transformed by N×N DCT. Ct=DCT(C). The coefficients to be altered X = x1 x2 … xm (m coefficients in the Ct except DC, m: extract pattern length) How to choose X: many heuristics In zigzag order choose an interval length = m In this homework we suggest you to use it Max m coefficient in zigzag order Random sample m coefficient m coefficient with largest DCT value …

Improved Spread Spectrum Define The scaling parameter α (α = 0.1~100 ?) The interference control parameter λ Around 1 will have better performance Extract pattern: 𝑢 = ( ±1 ⋮ ±1 ), Length of 𝑢 = m 𝑢 can be generate by an N(0,1) + sign(.) We can use 𝑢 to spread b into many frequency band and extract it from embedded image

Improved Spread Spectrum Basic Idea 𝑠 = 𝑥 + (α * b -λ * 𝑥 , 𝑢 𝑢 , 𝑢 ) * 𝑢 𝑠 , 𝑥 , α, b, 𝑢 : the same as Spread Spectrum λ: control parameter of cover interference <a, b>: inner product of vector a and b Use lambda term to remove cover interference

Improved Spread Spectrum Embedding Illustrate Given an image I Transform color domain from rgb to ycbcr, and then we chose y channel to embed our watermark Perform 2-D DCT to y channel Chose m elements from middle band to get 𝑥 Middle Band = 𝑥 Low Band High Band 𝑥 = ( 𝑥 1 ⋮ 𝑥 𝑚 )

Improved Spread Spectrum Embedding Illustrate Given an Watermarking bit b Use pattern 𝑢 to spread b’s information into many frequency band 𝑠 = 𝑥 + (α * b -λ * 𝑥 , 𝑢 𝑢 , 𝑢 ) * 𝑢 Where 𝑠 = ( 𝑠 1 ⋮ 𝑠 𝑚 ) 𝑥 =( 𝑥 1 ⋮ 𝑥 𝑚 ) 𝑢 =( ±1 ⋮ ±1 ) α = 0.1~100 λ = around 1 b = ±1

Improved Spread Spectrum Extracting Illustrate Recall: Embedding function 𝑠 = 𝑥 + (α * b -λ * 𝑥 , 𝑢 𝑢 , 𝑢 ) * 𝑢 Calculate similarity sim = 𝑠 , 𝑢 𝑢 , 𝑢 Basically 𝑥 , 𝑢 𝑢 , 𝑢 can be canceled by -λ 𝑥 , 𝑢 𝑢 , 𝑢 𝑢 , 𝑢 𝑢 , 𝑢 We can get sim = α * b * 𝑢 , 𝑢 𝑢 , 𝑢 = α * b Use sign(sim) to extract watermark bit b

Improved Spread Spectrum So far, we can embed just “1” bit message into image But, how can we embed “n” bits? 3 Ways Code division Use different extract pattern(orthogonal extract patterns are suggest) Frequency division Embed message into different frequency band Spatial division Slice image into many blocks each block embeds 1 bit message In this homework we use this method

Measurements We always have three dimensions in measurement stage Capacity Fidelity Robustness When measuring one dimension, you must fix the others When compare two dimensions, you must fix the other

Measurements Measurements for Capacity Amount of message that embedded in cover image How to improve capacity The more blocks you slice the original image, the more bits you can embed into it As you know, code division, frequency division methods can also achieve capacity requirement.

Measurements Measurements for Fidelity Quality of watermarked image Use PSNR value between original image and marked image Reference website https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio Code: Call PSNR(imageA, imageB) in MATLAB or Find PSNR code in web and use it How to improve fidelity Consider influence of cover images not just use additive operation to add watermark into it Consider Human Visual System(ex: perceptual model) Embedding in other domain(ex: wavelet based approach)

Measurements Measurements for Robustness Resistance to several attacks Use bit error rate BER to measurement performance Define: 𝑊 : original watermark( ±1 ⋯ ±1 )T 𝑊′ : extract watermark( ±1 ⋯ ±1 )T L: watermark length BER: (amount of difference bit of 𝑊 and 𝑊′ ) / L How to improve Robustness Use adaptive alpha term Use ECC(error correction code) Consider JPEG effect(ex: quantization based approach) Affine-Resistant Watermarking(Lecture 9)

Attacks Lossy Compression Geometric Distortion Cropping JPEG compression Geometric Distortion Rotation Shifting Scaling Affine transform Cropping Image Processing Blurring …

Homework1 Rules Deadline: Hand-in instructions: 2016/11/28 14:00 (suggest) Before the week of final exam(I will strictly grade your score) Hand-in instructions: Program: MATLAB code(suggest), other languages are welcome You will have to demo your work on your laptop if I cant run it Report: PDF file(strongly suggest), others are welcome You will get zero on this homework if I cant open this report ! Zip all program files, reports into one file and sent to ipr@cmlab.csie.ntu.edu.tw Title the mail as: [MMSEC]2016HW1_studentID Name the attached file as: [MMSEC]2016HW1_studentID.zip studentID example: R04922106

Homework1 Grading Criteria Program (30%): embed and extract ISS functions A main program to perform embed and extract process Report (70%): How to execute your code Any special method you implement besides the basic ISS scheme Test parameters used in ISS scheme Test capacity, fidelity and robustness of your watermarking scheme Compare Improved Spread Spectrum with Spread Spectrum Compare the influence of attacks on your watermarking scheme At least 6 types of attacks Others

Homework1 Baseline Code: ISS scheme Use block DCT to embed message bits into each block Use sim = 𝑠 , 𝑢 𝑢 , 𝑢 to extract message m Feel free to try different heuristic to chose embedding position Feel free to try code division or frequency division methods to enhance capacity Report: Briefly explain what have you done Feel free to try as many as possible experiments about ISS watermarking Use images to perform your results is better than just plot test records It is fine to write your report in Chinese, but English is preferable Have fun with this homework!! When life gives you lemons, make lemonade

Bonus Please propose a blind watermarking scheme of Chiou-Ting Hsu and Ja-Ling Wu, "Hidden Digital Watermarks in Images," IEEE Trans. On Image Processing, Vol.8, No.1, pp.58~68 January. 1999. P.S. You can just write down your opinions of the new scheme Weclome to implement the new scheme

Advanced Reading Watermarking on other multimedia References: Video No limitation on multimedia materials. References: Video “Digital Video Watermarking in P-Frames with Controlled Video Bit-Rate Increase”, IEEE Transactions on Information Forensics and Security, 2008. “Blind MPEG-2 Video Watermarking Robust Against Geometric Attacks: A Set of Approaches in DCT Domain”, IEEE Transactions on Image Processing, 2006. Audio “Spread-Spectrum Watermarking of Audio Signals”, IEEE Transactions on Signal Processing, 2003. “Watermarked Movie Soundtrack Finds the Position of the Camcorder in a Theater”, IEEE Transactions on Multimedia, 2009. Graphics “Watermarking Three-Dimensional Polygonal Models Through Geometric and Topological Modifications”, IEEE Journal on Selected Areas in Communications, 1998. Text “Data Hiding in Binary Image for Authentication and Annotation”, IEEE Transactions on Multimedia, 2004.